Results 41 to 50 of about 3,123 (260)

Compound Fault Diagnosis of Gearbox Based on RLMD and SSA-PNN [PDF]

Mathematical Problems in Engineering, 2021
In order to solve the difficulty in the classification of gearbox compound faults, a gearbox fault diagnosis method based on the sparrow search algorithm (SSA) improved probabilistic neural network (PNN) is proposed. Firstly, the gearbox fault signal is decomposed into a series of product functions (PFs) by robust local mean decomposition (RLMD). Then,
Shitong Liang, Jie Ma
openaire   +1 more source

A Hybrid Feature Selection and Multi-Label Driven Intelligent Fault Diagnosis Method for Gearbox

, 2023
Gearboxes are utilized in practically all complicated machinery equipment because they have great transmission accuracy and load capacities, so their failure frequently results in significant financial losses.
Xiangfeng Zhang, Zhiyu Zhang, Di Liu, Hong Jiang   +3 more
core   +1 more source

ResGRU: A Novel Hybrid Deep Learning Model for Compound Fault Diagnosis in Photovoltaic Arrays Considering Dust Impact. [PDF]

Sensors (Basel)
With the widespread deployment of photovoltaic (PV) power stations, timely identification and rectification of module defects are crucial for extending service life and preserving efficiency.
Liu X, Goh HH, Xie H, He T, Yew WK, Zhang D, Dai W, Kurniawan TA.   +7 more
europepmc   +2 more sources

Research on Rotating Machinery Fault Diagnosis Based on an Improved Eulerian Video Motion Magnification

, 2023
Rotating machinery condition monitoring and fault diagnosis are important bases for maintenance decisions, as the vibrations generated during operation are usually imperceptible to the naked eye.
Haifeng Zhao, Dengpan Jiang, Xiaorui Zhang, Jin Gu   +3 more
core   +1 more source

Train Axlebox Bearing Fault Diagnosis Based on MSC–SGMD

, 2023
Train axlebox bearings are subject to harsh service conditions, and the difficulty of diagnosing compound faults has brought greater challenges to the maintenance of high–quality train performance. In this paper, based on the traditional symplectic
Yongliang Bai, Hai Xue, Jiangtao Chen
core   +1 more source

Compound Faults Feature Extraction for Rolling Bearings Based on Parallel Dual-Q-Factors and the Improved Maximum Correlated Kurtosis Deconvolution

Applied Sciences, 2019
Vibration analysis is one of the main effective ways for rolling bearing fault diagnosis, and a challenge is how to accurately separate the inner and outer race fault features from noisy compound faults signals.
Lingli Cui, Jianxi Du, Na Yang, Yonggang Xu, Liuyang Song   +4 more
doaj   +1 more source

The Single-channel blind source separation based on VMD and Tukey M estimation for rolling bearing composite fault diagnosis

Measurement + Control, 2023
Rolling bearing is one of the core components in rotating machinery, and its running status directly affects the operation of the whole equipment. Faults of rolling bearings in the actual working process are often multiple faults. To effectively separate
Yaping Wang, Qisong Zhang, Ruofan Cao, Sheng Zhang, Shisong Li, Di Xu   +5 more
doaj   +1 more source

Sparsity-Oriented Nonconvex Nonseparable Regularization for Rolling Bearing Compound Fault under Noisy Environment

Shock and Vibration, 2020
Rolling bearing is widely used in rotating machinery and, at the same time, it is easy to be damaged due to harsh operating environments and conditions. As a result, rolling bearing is critical to the safe operation of the machinery devices.
Xiaocheng Li, Jingcheng Wang, Hongyuan Wang   +2 more
doaj   +1 more source

Blind Fault Extraction of Rolling-Bearing Compound Fault Based on Improved Morphological Filtering and Sparse Component Analysis

, 2022
In order to effectively separate and extract bearing composite faults, in view of the non-linearity, strong interference and unknown number of fault source signals of the measured fault signals, a composite fault-diagnosis blind extraction method based ...
Xie, Wensong, Jun Zhou, Zhou, Jun, Tao Liu, Wensong Xie, Liu, Tao   +5 more
core   +1 more source

Intelligent Diagnosis of Rolling Bearings Fault Based on Multisignal Fusion and MTF-ResNet

Sensors, 2023
Existing diagnosis methods for bearing faults often neglect the temporal correlation of signals, resulting in easy loss of crucial information. Moreover, these methods struggle to adapt to complex working conditions for bearing fault feature extraction ...
Kecheng He, Yanwei Xu, Yun Wang, Junhua Wang, Tancheng Xie   +4 more
doaj   +1 more source